{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy,datetime,random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fitness(genes):\n",
    "    return genes.count(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Chromosome:\n",
    "    def __init__(self, genes, fitness):\n",
    "        self.Genes = genes\n",
    "        self.Fitness = fitness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def display(candidate, startTime):\n",
    "    timeDiff = datetime.datetime.now() - startTime\n",
    "    print(\"{}...{}\\t{:3.2f}\\t{}\".format(\n",
    "        ''.join(map(str, candidate.Genes[:15])),\n",
    "        ''.join(map(str, candidate.Genes[-15:])),\n",
    "        candidate.Fitness,\n",
    "        timeDiff))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mutate(parent,idxlist):\n",
    "    childGenes = parent.Genes[:]\n",
    "    while True:\n",
    "        index = random.randrange(0, len(parent.Genes),1)\n",
    "        if index in idxlist:\n",
    "            pass\n",
    "        else:\n",
    "            break\n",
    "    newGene, alternate = random.sample([0,1], 2)\n",
    "    childGenes[index] = alternate if newGene == childGenes[index] else newGene\n",
    "    fitness = get_fitness(childGenes)\n",
    "    return (Chromosome(childGenes, fitness),index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_best():\n",
    "    oneIndex = []\n",
    "    random.seed()\n",
    "    startTime = datetime.datetime.now()\n",
    "    c1 = numpy.random.randint(0,2,(100)).tolist()\n",
    "    bestParent = Chromosome(c1,get_fitness(c1))\n",
    "    if bestParent.Fitness >= 100:\n",
    "        return bestParent\n",
    "    num = 0\n",
    "    while True:\n",
    "        num +=1\n",
    "        child,idx = mutate(bestParent,oneIndex)\n",
    "        if bestParent.Fitness >= child.Fitness:\n",
    "            continue\n",
    "        oneIndex.append(idx)\n",
    "        #display(bestParent,startTime)\n",
    "        if child.Fitness >= 100:\n",
    "            display(child,startTime)\n",
    "            return (child,num)\n",
    "        bestParent = child\n",
    "    display(bestParent,startTime)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "000000000000000...000000000000000\t100.00\t0:00:00.001994\n",
      "100 , 231\n"
     ]
    }
   ],
   "source": [
    "b = get_best()\n",
    "print(b[0].Fitness,\",\",b[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     "name": "stdout",
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      "000000000000000...000000000000000\t100.00\t0:00:00.002031\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "000000000000000...000000000000000\t100.00\t0:00:00.001959\n",
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      "000000000000000...000000000000000\t100.00\t0:00:00.003014\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.001000\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.002989\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.002959\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.003026\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.002958\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.003026\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.001974\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.002976\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.002005\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.003982\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.003988\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.001031\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.002993\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.001994\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.001997\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.003954\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.004005\n",
      "000000000000000...000000000000000\t100.00\t0:00:00.002943\n"
     ]
    }
   ],
   "source": [
    "n = []\n",
    "for i in range(1000):\n",
    "    n.append(get_best()[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 95., 385., 315., 139.,  45.,  10.,   5.,   3.,   1.,   2.]),\n",
       " array([142. , 201.3, 260.6, 319.9, 379.2, 438.5, 497.8, 557.1, 616.4,\n",
       "        675.7, 735. ]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "274.921"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numpy.mean(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
